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Reducing truck emissions at container terminals in a low carbon economy: This study proposes a methodology to optimize truck arrival patterns to reduce emissions from idling truck engines at marine container terminals. A bi-objective model is developed minimizing both truck waiting times and truck arrival pattern change. The truck waiting time is estimated via a queueing network. Based on the waiting time, truck idling emissions are estimated. The proposed methodology is evaluated with a case study, where truck arrival rates vary over time.

We propose a Genetic Algorithm based heuristic to solve the resulting problem. Result shows that, a small shift of truck arrivals can significantly reduce truck emissions, especially at the gate. Low-carbon production is one of the dominating issues in the sustainable development of the food industry with high energy consumption [1][2][3], especially in the table grapes cold chain. Low-carbon production is a green and sustainable development mode with lower greenhouse gas GHG emissions for the cold chain [4] [5] [6].

The table grapes cold chain is a special system that enables table grapes to always be stored at a prescribed low temperature to reduce the loss of table grapes and ensure their quality and safety [7][8][9]. In order to reduce emissions from idling trucks, Chen et al. Some of the recent existing papers developed mathematical models and simulations by evaluating different CHE options with the goal of diminishing the energy expense. Railway safety by designing the layout of inland terminals with dangerous goods connected with the rail transport system.

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